Zoran J N Steinmann

Datos Biográficos

ID6569461
NOMBREZoran J N Steinmann
NOMBRESZoran J N
APELLIDOSteinmann
FIRMASTEINMANN Z J N
AFILIACIONESRadboud University Nijmegen
ORCID0000-0001-8606-917X
VERIFICADOSí
TOTAL DE OBRAS8
TOTAL DE CITAS4
TOTAL COMO AUTOR8
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2014
AÑO MÁS RECIENTE DE PUBLICACIÓN2021
ÍNDICE H1

  • Identifying regional drivers of future land-based biodiversity footprints

    Open AccessSandra Marquardt, Sandra G Marquardt et al.ARTICLEGlobal Environmental Change2021Citada por: 4Referencias: 11

    Biodiversity footprints quantify the impacts on ecosystems caused by final consumption in a region, accounting for imports and exports. Up to now, footprint analyses have typically been applied to analyze past or present consumption patterns. Here, we quantify future land-based biodiversity footprints associated with three diverging Shared Socio-economic Pathways (SSPs), using loss in Biodiversity Intactness Index (BII) as an indicator of biodive…

  • The climate change mitigation potential of bioenergy with carbon capture and storage

    Open AccessSteef V Hanssen, Vassilis Daioglou et al.ARTICLENature Climate Change2020

  • Lc‐impact

    Open AccessFrancesca Verones, Stefanie Hellweg et al.ARTICLEJournal of Industrial Ecology2020

    Life cycle impact assessment (LCIA) is a lively field of research, and data and models are continuously improved in terms of impact pathways covered, reliability, and spatial detail. However, many of these advancements are scattered throughout the scientific literature, making it difficult for practitioners to apply the new models. Here, we present the LC-IMPACT method that provides characterization factors at the damage level for 11 impact categ…

  • The influence of consumer behavior on energy, greenhouse gas, and water footprints of showering

    Open AccessSadegh Shahmohammadi, Zoran J N Steinmann et al.ARTICLEJournal of Industrial Ecology2019

    Understanding variability in consumer behavior can provide further insights into how to effectively reduce environmental footprints related to household activities. Here, we developed a stochastic model to quantify the energy, greenhouse gas (GHG), and water consumption footprints of showering in four different countries (Australia, Switzerland, the United Kingdom, and the United States of America). We assessed the influence of two broadly distin…

  • Headline Environmental Indicators Revisited with the Global Multi‐Regional Input‐Output Database Exiobase

    Open AccessZoran J N Steinmann, Aafke M Schipper et al.ARTICLEJournal of Industrial Ecology2018

    Environmentally extended multiregion input‐output (EEMRIO) databases are used to quantify numerous environmental pressures and impacts from a consumption perspective. However, for targeted communication with decision makers, large sets of impact indicators are unfavorable. Small sets of headline indicators have been proposed to guide environmental policy, but these may not cover all relevant aspects of environmental impact. The aim of our study w…

  • ReCiPe2016

    Open AccessMark A J Huijbregts, Zoran J N Steinmann et al.ARTICLEThe International Journal of Life…2017

    Life cycle impact assessment (LCIA) translates emissions and resource extractions into a limited number of environmental impact scores by means of so-called characterisation factors. There are two mainstream ways to derive characterisation factors, i.e. at midpoint level and at endpoint level. To further progress LCIA method development, we updated the ReCiPe2008 method to its version of 2016. This paper provides an overview of the key elements o…

  • Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale

    Open AccessMara Hauck, Zoran J N Steinmann et al.ARTICLEJournal of Industrial Ecology2017

    Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricit…

  • How to quantify uncertainty and variability in life cycle assessment

    Open AccessMara Hauck, Zoran J N Steinmann et al.ARTICLEEnvironmental Research Letters2014

    n Contains fulltext :\n 133118.pdf (Publisher’s version ) (Open Access)\n \n Contains fulltext :\n 133118.pdf (Author’s version preprint ) (Open Access)\n \n Contains fulltext :\n 133118(supplement).pdf (Author’s version preprint ) (Open Access)\n